3 papers
cs.AI2026
Latent Action Reparameterization for Efficient Agent Inference
Wenhao Huang, Qingwen Zeng, Qiyue Chen +11
Large language model (LLM) agents often rely on long sequences of low-level textual actions, resulting in large effective decision horizons and high inference cost. While prior wor…
cs.SE2026
Firefly: Illuminating Large-Scale Verified Tool-Call Data Generation from Real APIs
Yuxuan Lu, Ziyi Wang, Yingzhou Lu +12
Training tool-calling agents requires large-scale trajectory data with verifiable labels, yet existing approaches either synthesize environments that diverge from real API behavior…
cs.LG2025
Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction
Yong Lin, Shange Tang, Bohan Lyu +17
We introduce Goedel-Prover-V2, a series of open-source language models that set a new state-of-the-art in automated theorem proving. Built on the standard expert iteration and rein…